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Deriving seasonal dynamics in ecosystem properties of semi-arid savanna grasslands from in situ-based hyperspectral reflectance

机译:利用原位高光谱反射率推导半干旱热带稀树草原草原生态系统属性的季节动态

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摘要

This paper investigates how hyperspectral reflectance (between 350 and 1800 nm) can be used to infer ecosystem properties for a semi-arid savanna grassland in West Africa using a unique in situ-based multi-angular data set of hemispherical conical reflectance factor (HCRF) measurements. Relationships between seasonal dynamics in hyperspectral HCRF and ecosystem properties (biomass, gross primary productivity (GPP), light use efficiency (LUE), and fraction of photosynthetically active radiation absorbed by vegetation (FAPAR)) were analysed. HCRF data (rho) were used to study the relationship between normalised difference spectral indices (NDSIs) and the measured ecosystem properties. Finally, the effects of variable sun sensor viewing geometry on different NDSI wavelength combinations were analysed. The wavelengths with the strongest correlation to seasonal dynamics in ecosystem properties were shortwave infrared (biomass), the peak absorption band for chlorophyll a and b (at 682 nm) (GPP), the oxygen A band at 761 nm used for estimating chlorophyll fluorescence (GPP and LUE), and blue wavelengths (rho(412)) (FAPAR). The NDSI with the strongest correlation to (i) biomass combined rededge HCRF (rho(705)) with green HCRF (rho(587)), (ii) GPP combined wavelengths at the peak of green reflection (rho(518), rho(556)), (iii) LUE combined red (rho(688)) with blue HCRF (rho(436)), and (iv) FAPAR combined blue (rho(399)) and near-infrared (rho(1295)) wavelengths. NDSIs combining near infrared and shortwave infrared were strongly affected by solar zenith an-gles and sensor viewing geometry, as were many combinations of visible wavelengths. This study provides analyses based upon novel multi-angular hyperspectral data for validation of Earth-observation-based properties of semi-arid ecosystems, as well as insights for designing spectral characteristics of future sensors for ecosystem monitoring.
机译:本文研究如何使用独特的基于半球圆锥反射系数(HCRF)的基于原位的多角度数据集,利用高光谱反射率(在350至1800 nm之间)推断西非半干旱稀树草原的生态系统特性测量。分析了高光谱HCRF的季节动态与生态系统特性(生物量,总初级生产力(GPP),光利用效率(LUE)以及植被吸收的光合有效辐射比例(FAPAR))之间的关系。 HCRF数据(rho)用于研究归一化差异光谱指数(NDSI)与测得的生态系统特性之间的关系。最后,分析了可变太阳传感器观察几何形状对不同NDSI波长组合的影响。与生态系统特性的季节动态最相关的波长是短波红外(生物量),叶绿素a和b的峰值吸收带(在682 nm)(GPP),用于估计叶绿素荧光的761 nm的氧A带( GPP和LUE)以及蓝色波长(rho(412))(FAPAR)。与(i)生物质结合的红边HCRF(rho(705))和绿色HCRF(rho(587)),(ii)GPP在绿色反射峰(rho(518),rho( 556)),(iii)LUE将红色(rho(688))与蓝色HCRF(rho(436))组合在一起,以及(iv)FAPAR将蓝色(rho(399))和近红外(rho(1295))波长组合在一起。结合近红外和短波红外的NDSI受到太阳天顶角和传感器观察几何形状的强烈影响,可见光波长的许多组合也受到很大影响。这项研究提供了基于新颖的多角度高光谱数据进行的分析,以验证半干旱生态系统基于地球观测的特性,并为设计未来用于生态系统监测的传感器的光谱特性提供了见识。

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